1. Field of the Invention
This invention involves an improved method and apparatus for radar signal processing. In particular, the present invention pertains to a binary branching technique of noncoherent integration radar signal processing with reduced computational complexity.
2. State of the Art
Radar systems detect distant target objects by transmitting signals and detecting the echos reflected back from the target object. Detection of a target object can include, for instance, determining target object data such as position, direction of movement, velocity and acceleration. Conventional radar systems transmit electromagnetic signals with, for example, predetermined frequencies in the megahertz range up to light wave frequencies in the visible spectrum. The transmitted radar signal of predetermined frequencies may include pulses or waveforms transmitted at varying frequencies. Such varying frequencies may be used, for instance, to implement linear frequency modulated chirp pulses, signal encoding schemes, or the like. The radar system transmitter and receiver can either be co-located or located at different positions.
Signal strength of the return signal varies inversely to the fourth power with the distance R between the radar system and the target (1/R4). As a result, the signal strength of return signals reflected from the target tend to be relatively weak in comparison to the transmitted signal.
Signal strength is important in discerning information about a target object. Signal strength and signal quality are affected by a number of radar parameters and target variables, in addition to being affected by the distance between the radar system and the target. For instance, the parameters of radar aperture, transmit power and amplifier efficiencies each affect the ability of a radar system to detect return signals. Target characteristics pertaining to target size and shape, the target object material, target velocity and acceleration, each affect the quality and strength of the return signal. Small, fast moving, distant targets-such as missiles, for instancexe2x80x94can be especially challenging to detect. The return signals of such target objects become very difficult to detect as they approach the level of noise due to background interference or electromagnetic clutter.
Return signals can be subjected to signal processing to discern their Doppler characteristics and determine the position, velocity and acceleration of the target object. As the signal-to-noise ratio (SNR) decreases, signal processing tends to become more important for signal detection. But signal processing also becomes more difficult as signal strength decreases because the SNR becomes smaller and the return signal gets lost in the background noise.
Signal processing may be used to detect low SNR signals, especially if the low SNR signal has few unknown variables. In general, low SNR signals with fewer unknown variables are easier to detect than low SNR signals with more unknown variables. For example, signals having a known acceleration value are easier to detect than signals with an unknown acceleration component.
One way of reducing the unknown characteristics of a return signal pertains to signal phase. To aid in signal processing, radar signals are often coherently transmitted. Signal coherence simply refers to a continuity of phase from one transmitted signal to the next, as if the signals had been chopped out of the same continuous waveform. Use of coherent signals enables the detection of Doppler shifting due to changes in relative velocity between the radar system and the target object.
Signal processing generally involves transforming received signals from the time domain to a frequency domain representation through a process of coherent integration such as a fast Fourier transform (FFT) filter. Once the received signals have been transformed into the frequency domain, signal processing can be used to analyze the Doppler shift of coherent signals to determine information about the target object, so long as the return signals have sufficient signal strength.
FIG. 1A is an FFT frequency domain representation of a received signal. The FFT shown in FIG. 1A indicates the relative velocity between the radar system and the target object. Target objects with higher velocities relative to the radar system have higher frequencies, and are shown shifted to the right. Target objects moving more slowly relative to the radar system have lower frequencies, and are shown shifted to the left.
By analyzing the FFTs corresponding to different time segments, changes in target velocity can be determined. This allows for an approximate determination of acceleration. However, to make such an approximate acceleration determination using a conventional radar signal processor, the received signal must be strong enough for detection in each FFT. If the SNR is too low for target detection in the FFTs of different time segments, no velocity comparison can be made, as required for determining acceleration.
In conventional radar systems, signal processing can be used to detect return signals and determine an unknown target acceleration for return signals characterized by high SNR. Conventional radar systems may also be able to detect the presence of return signals characterized by low SNR, but only if the acceleration component of the return signal is known.
The Applicants recognize that if acceleration is unknown for low SNR signals, the computational complexity of signal processing becomes much more extensive, to the extent of being beyond the computational capabilities of today""s technology. Therefore, Applicants identify one drawback of conventional radar systems as being the inability to detect low SNR return signals having unknown acceleration components. In other words, conventional radar systems lack a means of reducing the computational burdens which would be associated with signal processing return signals characterized by low SNR and having unknown acceleration characteristics.
The present invention is directed to reducing the computational burdens associated with processing return signals of unknown acceleration and having low SNRs. The present invention provides a more efficient way of performing signal processing including the operation of non-coherent integration.
Generally speaking, exemplary embodiments are directed to radar signal processing according to a predetermined scheme in which partially processed received signal data is selectively stored and reused. By doing so, redundant processing is reduced, thus enabling the radar signal processor to detect signals with an unknown acceleration component using a reasonable number of signal processing computations.
The present invention is directed to a radar signal processing method and system for detecting target objects. According to one embodiment, radar signals are transmitted from a radar system in a predetermined frequency scheme. The radar system receives signals within a frequency band which includes frequencies of the predetermined frequency scheme and frequencies of return signals echoed from the target object. The frequencies of the return signals may be frequency (Doppler) shifted from the predetermined frequency scheme by unknown amounts, making detection by conventional methods computationally burdensome or even impossible due to the combination of uncertainty in both Doppler velocity and acceleration. The received signals are then coherently integrated to transform them from time domain data into frequency domain templates of data. Once the received signals are in the form of frequency domain templates, they are arranged into an array matrix. The data of the frequency domain templates are processed to form presums, which are stored for use in forming higher level presums and for forming acceleration bins. Once the acceleration bins have been formed, they are analyzed to detect the presence of target object return signals.